[R] Wilks Lamba
Sven Garbade
garbade at psy.uni-muenchen.de
Fri Mar 22 01:06:20 CET 2002
Peter Dalgaard BSA wrote:
>
> Sven Garbade <garbade at psy.uni-muenchen.de> writes:
>
> > Hi all,
> >
> > I can't figure out how to compute Wilks Lambda in a one way repeated
> > measure design. My matrix looks like:
> >
> > > t2.m
> > Blank ECR ENC UEA UED
> > 1 -0.15 0.14 0.16 0.09 0.14
> > 2 0.30 0.08 0.14 0.14 0.14
> > [...]
> >
> > where each row is a case and the columns are levels of one factor (named
> > trial):
> >
> > > t2.fit <- manova(t2.m ~ 1)
> > > summary(t2.fit, intercept=T, test="Wilks")
> > Df Wilks approx F num Df den Df Pr(>F)
> > (Intercept) 1 0.26869 1.63302 5 3 0.3642
> > Residuals 7
> >
> > ist this correct? I ask because SPSS gives me a different result:
> >
> > Effect: Trial
> > Wilks: 0.392
> > F: 1.554
> > Df: 4
> > error Df: 4
> > Pr: 0.340
> >
> > Thanks for any hints, Sven
>
> Hmm. The ways of SPSS are sometimes mysterious, but the Df suggest
> that you're testing that the 5 variables all have mean zero, whereas
> SPSS might be testing whether they have the *same* mean. You can check
> that by looking at
>
> t2.m2 <- t2.m[,-1] - t2.m[,1]
> t2.fit <- manova(t2.m ~ 1)
Thanks, that is exactly what I was looking for. Indeed I need to test
that the 5 variables all have mean zero. But I haven't found anything in
the SPPS doc about what SPSS did, so I got confused.
Thanks & regards, Sven
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